4 citations · 4 across the 4 of their papers we have counts for
4 papers
Making a Spiking Net Work: Robust brain-like unsupervised machine learning
Peter G. Stratton, Andrew Wabnitz, Chip Essam +2
The surge in interest in Artificial Intelligence (AI) over the past decade has been driven almost exclusively by advances in Artificial Neural Networks (ANNs). While ANNs set state…
A Trainable Neuromorphic Integrated Circuit that Exploits Device Mismatch
Chetan Singh Thakur, Runchun Wang, Tara Julia Hamilton +2
Random device mismatch that arises as a result of scaling of the CMOS (complementary metal-oxide semi-conductor) technology into the deep submicron regime degrades the accuracy of…
Turn Down that Noise: Synaptic Encoding of Afferent SNR in a Single Spiking Neuron
Saeed Afshar, Libin George, Jonathan Tapson +3
We have added a simplified neuromorphic model of Spike Time Dependent Plasticity (STDP) to the Synapto-dendritic Kernel Adapting Neuron (SKAN). The resulting neuron model is the fi…
Racing to Learn: Statistical Inference and Learning in a Single Spiking Neuron with Adaptive Kernels
Saeed Afshar, Libin George, Jonathan Tapson +2
This paper describes the Synapto-dendritic Kernel Adapting Neuron (SKAN), a simple spiking neuron model that performs statistical inference and unsupervised learning of spatiotempo…